import pandas as pd
df = pd.read_csv('vehicle_positions.txt')

stops = pd.read_csv('Bus_Stops.csv')

stops.dropna(subset= ['stop_lat', 'stop_lon', 'Routes'], inplace = True)

df.dropna(inplace=True)

df.start_date = df.start_date.astype(int)

df.loc[df['route_id'].isin(['34', '66', '40'])]

	feed_time	trip_id	vehicle.id	start_time	start_date	route_id	direction_id	schedule_relationship	latitude	longitude	bearing	stop_id	current_stop_sequence	current_status	timestamp
12	1.578631e+09	42844620	y1921	23:20:00	20200109	66	0	0	42.355228	-71.133087	0.0	1112	25	2	1578630948
28	1.578631e+09	42843616	y1834	23:00:00	20200109	66	1	0	42.329590	-71.086380	135.0	11259	35	2	1578630949
42	1.578631e+09	42843540	y1898	23:05:00	20200109	66	0	0	42.374928	-71.118599	0.0	2168	33	2	1578630954
155	1.578631e+09	42844560	y1830	23:30:00	20200109	66	1	0	42.363678	-71.129158	0.0	2553	5	2	1578630960
225	1.578631e+09	42843598	y1875	23:15:00	20200109	66	1	0	42.333935	-71.105171	0.0	1317	27	2	1578630956
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
12010948	1.579309e+09	42843869	y1908	19:07:00	20200117	66	0	0	42.367096	-71.124931	35.0	2564	31	2	1579308532
12010973	1.579309e+09	42843786	y1811	19:29:00	20200117	66	1	0	42.353069	-71.132950	93.0	10928	14	2	1579308533
12011015	1.579309e+09	42989065	y1640	19:48:00	20200117	34	1	0	42.257122	-71.169174	182.0	10835	2	2	1579308534
12011027	1.579309e+09	42843785	y1787	19:17:00	20200117	66	1	0	42.333561	-71.118820	135.0	1313	23	2	1579308498
12011071	1.579309e+09	42987791	y1686	19:35:00	20200117	34	0	0	42.278450	-71.136894	0.0	606	13	2	1579308523

267808 rows × 15 columns

stops34 = stops[stops['Routes'].str.contains('34')]

fig = px.scatter_mapbox(
    df.loc[df['route_id'].isin(['34'])],
    lat="latitude",
    lon="longitude",
    color="vehicle.id",
    hover_data=["direction_id", "vehicle.id"],  
    color_continuous_scale=px.colors.cyclical.IceFire,
    size_max=15,
    zoom=10,
    animation_frame="start_date",
    title='Bus #34',
)
fig.show()

fig = px.scatter_mapbox(
    df.loc[df['route_id'].isin(['66'])],
    lat="latitude",
    lon="longitude",
    color="vehicle.id",
    hover_data=["direction_id", "vehicle.id"],  
    color_continuous_scale=px.colors.cyclical.IceFire,
    size_max=15,
    zoom=10,
    animation_frame="start_date",
    title='Bus #66',
)
fig.show()

fig = px.scatter_mapbox(
    df.loc[df['route_id'].isin(['59'])],
    lat="latitude",
    lon="longitude",
    color="vehicle.id",
    hover_data=["direction_id", "vehicle.id", 'route_id', 'schedule_relationship', 'current_status'],  
    color_continuous_scale=px.colors.cyclical.IceFire,
    size_max=15,
    zoom=10,
    animation_frame="start_date",
    title='Bus #59',
)
fig.show()

import plotly.express as px

px.set_mapbox_access_token(open(".mapbox_token").read())
fig = px.scatter_mapbox(
    df.loc[df['route_id'].isin(['34', '66'])],
    lat="latitude",
    lon="longitude",
    color="route_id",
    hover_data=["direction_id", "vehicle.id"],  # size="car_hours",
    color_continuous_scale=px.colors.cyclical.IceFire,
    size_max=15,
    zoom=10,
    animation_frame="start_date"
)
#fig.add_scattermapbox(
#    below="''",
    #marker={"symbol": ["circle"], 'size' = 15},
#    lat=stops34.stop_lat,
#    lon=stops34.stop_lon,
#)
fig.show()

import numpy as np
import datetime
import time
from datetime import date

#pd.to_datetime(df66.index)
datetime.datetime.fromtimestamp(df66.feed_time[752])
#datetime.datetime.fromtimestamp(datetime.datetime.now().timestamp())

datetime.datetime(2020, 1, 9, 23, 36, 44, 982151)